The present invention relates generally to a three-point method and apparatus for efficiently creating robust magnetic field maps of a region-of-interest (ROI).
When a substance such as human tissue is subjected to a uniform magnetic field (polarizing field B0), the individual magnetic moments of the spins in the tissue attempt to align with this polarizing field, but precess about it in random order at their characteristic Larmor frequency. If the substance, or tissue, is subjected to a magnetic field (excitation field B1) which is in the x-y plane and which is near the Larmor frequency, the net aligned moment, or “longitudinal magnetization”, MZ, may be rotated, or “tipped”, into the x-y plane to produce a net transverse magnetic moment Mt. A signal is emitted by the excited spins after the excitation signal B1 is terminated and this signal may be received and processed to form an image.
When utilizing these signals to produce images, magnetic field gradients (Gx, Gy, and Gz) are employed. Typically, the region to be imaged is scanned by a sequence of measurement cycles in which these gradients vary according to the particular localization method being used. The resulting set of received NMR signals are digitized and processed to reconstruct the image using one of many well known reconstruction techniques.
Often, conventional magnetic resonance (MR) imaging acquires a small number of lines of k-space data after each RF excitation. The excitations are then repeated many times in order to cover k-space. With echo planar imaging (EPI), however, the complete k-space is acquired using a train of gradient recalled echoes that follow a single RF excitation. Such an acquisition sequence, however, often results in a longer readout period compared to other conventional sequences. In addition, EPI often results in low bandwidth per pixel in the phase encoding direction, making EPI more susceptible to artifacts in this direction. Further, off-resonance effects from local and main field inhomogeneities often cause phase accumulations over the longer readout periods of EPI.
The above-mentioned effects are spatially varying. As a result, geometric distortions often arise. For example, image voxels may be distorted through compression or stretching, depending on the local field gradients that they experience. This distortion causes the voxels to appear in the wrong place. As such, signal intensity may be either darker or brighter than it would be without the voxel distortion. The effects of these geometric distortions, which often scale linearly with main field strength, are prominent near paranasal sinuses, anterior orbits, the skull base, the liver-lung interface, air containing bowel loops, and other regions. Not only do the distortions have a negative impact on EPI data sets, they often hinder accurate registration of EPI data sets with functional information (e.g., BOLD) or structural information (e.g., white matter tracts) to anatomically correct non-EPI data sets.
Numerous techniques have been proposed to correct for geometric distortion. These techniques include the field mapping techniques, multi-reference techniques (such as multi-echo or PSF mapping), reversed gradient techniques, real-time techniques, and post-processing techniques. Each of these techniques, however, has their own drawbacks. For example, the multi-reference techniques typically measure distortion accurately; however, they require long acquisition times. Reversed gradient techniques, which acquire each data set twice in opposite directions to deduce the translation and intensity correction, are susceptible to noise in the data and often suffer from streaking artifacts. To serve as yet another example, real-time or single-shot techniques measure phase differences between multiple acquisitions following a single RF pulse; however, their resolution is limited by signal decay, especially at high fields.
The most commonly used correction technique has been field mapping, which measures variations in the magnetic field to calculate local pixel shifts in the image. The magnetic field map at each pixel is calculated from the slope of phase accumulation over time. In other words, the slope of phase accumulation between common points or pixels in two or more phase images is determined so that the magnetic field inhomogneities can be calculated. As such, a magnetic field map of a region of interest can be generated pixel by pixel. There are two main approaches to field mapping. The first approach acquires two phase images at different echo times, and then calculates a field map from the phase difference between these two phase images. If these two echo times are far apart, the range of phase accumulation between the two phase images may exceed 2π, thus causing phase wrapping in one of the phase images. In such an instance, phase unwrapping is needed. Phase unwrapping, however, can be problematic at disconnected and high susceptibility regions. On the other hand, if the two echo times are selected close to each other in order to avoid the need for phase unwrapping, the slope measurements are strongly influenced by the noise in the phase measurements. As such, multiple excitations are typically used to increase a signal-to-noise ratio (SNR) so that a more accurate magnetic field map may be obtained. The second approach entails the acquisition of a series of phase images, e.g., sixteen phase images, at different echo times, where the echo times are chosen such that phase wrapping between successive phase images does not occur. A line is then fit to the phase accumulation over time present in the phase images and the field map is calculated from the slope of the fit. The produced magnetic field maps may be robust; however, the time needed for mapping is increased due to the quantity of images acquired. Accordingly, efficiently obtaining a robust field map continues to be challenging.
It would therefore be desirable to have a system and method capable of calculating or creating a robust magnetic field map that minimizes the amount of time need to do so.